Update README.md

README.md

@@ -8,4 +8,187 @@ tags:
 - keras
 - ocr
 - ai captcha solving
----
+---
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [Ashish Chaudhary aka lolcod]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [https://github.com/lol-cod/solvingcaptchakeras]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+Direct Use
+The model is designed for solving 4-lettered captchas with an 80% accuracy rate. It can be directly employed for captcha-solving tasks without the need for fine-tuning or integration into a larger ecosystem or application.
+
+Downstream Use [optional]
+[More Information Needed]
+
+Out-of-Scope Use
+The model is not intended for tasks beyond solving 4-lettered captchas. It may not perform well on captchas with a different format or on tasks unrelated to captcha-solving.
+
+Bias, Risks, and Limitations
+The model's performance may vary based on the complexity and variability of captchas. It may not generalize well to captchas with different characteristics or lengths. Additionally, there is a risk of misclassification, leading to incorrect solutions. The model might be sensitive to changes in background, font styles, or other captcha variations.
+
+Recommendations
+Users, both direct and downstream, should be aware of the model's limitations and potential biases. It is recommended to assess the performance on a diverse set of captchas to understand the model's capabilities and shortcomings.
+
+How to Get Started with the Model
+To use the model, you can leverage the following code:
+
+python
+Copy code
+# Sample code for using the captcha-solving model
+import keras
+from keras.models import load_model
+from captcha_solver import solve_captcha
+
+# Load the pre-trained model
+model = load_model('captcha_model.h5')
+
+# Provide the captcha image as input
+captcha_image = 'path/to/your/captcha.png'
+solution = solve_captcha(model, captcha_image)
+
+# Print the solution
+print('Captcha Solution:', solution)
+[More Information Needed]
+
+Training Details
+Training Data
+The model was trained on a dataset of 4-lettered captchas. For more detailed information about the training data, refer to the accompanying Dataset Card.
+
+[More Information Needed]
+
+Training Procedure
+Preprocessing [optional]
+[More Information Needed]
+
+Training Hyperparameters
+Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+[More Information Needed]
+
+Speeds, Sizes, Times [optional]
+[More Information Needed]
+
+Evaluation
+[More Information Needed]
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+
+